Authors
Mingfeng Wu, Li Zhang, Xiong Wang, Shaohua Xu, Li Xie
Published in
Journal of visualized experiments : JoVE. Issue 235. Sep 15, 2026. Epub Sep 15, 2026.
Abstract
Pulmonary hypertension is a clinically important complication in elderly patients hospitalized with acute exacerbation of chronic obstructive pulmonary disease, but early risk estimation remains difficult in primary and resource-limited hospital settings. This retrospective cohort study developed and internally evaluated a routine-data-based nomogram for estimating pulmonary hypertension risk. A total of 230 elderly patients hospitalized with acute exacerbation of chronic obstructive pulmonary disease between May 2023 and May 2025 were analyzed. Patients were classified into non-pulmonary hypertension and pulmonary hypertension groups according to transthoracic echocardiographic findings. Demographic characteristics, comorbidities, complete blood count indices, coagulation markers, inflammatory markers, and cardiac stress markers were compared between groups. Candidate predictors were selected using univariate analysis, assessment of clinical relevance, redundancy assessment, and multivariable logistic regression. Four variables-neutrophil-to-lymphocyte ratio, B-type natriuretic peptide, D-dimer, and asthma history-were independently associated with pulmonary hypertension and were incorporated into the primary nomogram. The model demonstrated good discrimination, with an area under the receiver operating characteristic curve of 0.82. Decision curve analysis indicated potential net benefit across threshold probabilities of approximately 1% to 70%. Calibration findings required cautious interpretation due to residual calibration deviation. This workflow provides a practical approach for early pulmonary hypertension risk stratification in elderly patients hospitalized with acute exacerbation of chronic obstructive pulmonary disease. However, external validation and model recalibration are required before broader clinical implementation.
PMID:
42747060
Bibliographic data and abstract were imported from PubMed on 16 Sep 2026.
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